1. Technical Field
This disclosure relates to techniques for leakage detection in a hydraulic network and, more specifically, to leakage detection using pressure-dependant demand optimization where leakages are represented as pressure-dependant emitter flows.
2. Background
is Water utilities provide clean water to local communities and charge for the service by metering water consumptions or basing charges on the ratable value of customer's properties. However, not all water produced reaches the customers and generates revenue for water companies. Instead, a significant portion of it is lost, due to leakage from water mains and unauthorized water use. Water loss represents a major fraction of non-revenue water (NRW). Some estimate that the annual NRW volume lost is as high as 50 billion cubic meters from a world wide annual production of 300 billion cubic meters of potable water treated. The UK report that, on average, more than 15% of water produced in the UK is lost. Similarly, Canada reports that as much as $1 billion worth of drinking water disappears into the ground every year from leaky municipal water pipes in Ontario, and that 20 to 40 percent of all the water pumped through municipal water systems never reaches consumer taps. The fact that water companies and municipalities are losing such large quantities of water through leaky pipes undermines the conservation messages that many water utilities and municipalities are championing. Further, reduction of these losses also provides opportunities for water companies to reduce their carbon footprint and improve water infrastructure sustainability.
There are several known techniques for detecting where leakages are occurring in a water distribution system. These include (1) random or regular sounding surveys; (2) step-testing of sub-systems and (3) acoustic loggers surveys. Regular or random sounding surveys are time consuming and not always effective in focusing on areas with potential leaks. This is in part due to the fact that leakage technicians may end up looking for leaks in sections of the network where they are not prevalent, only realizing this after the fact. Further, step-testing needs to be conducted branch by branch, and generally must be undertaken during the period of minimum night flow (MNF) (e.g. 1:00 AM to 5:00 AM) is to avoid supply interruptions to the majority of customers. This may render step-testing to be inconvenient and expensive. Acoustic loggers can be either installed across the water distribution system or deployed at certain points. As such, loggers may be expensive in terms of the amount of equipment required or inconvenient in that a more limited amount of equipment must be repeatedly moved. Further, the effectiveness of acoustic loggers in sensing leaks can also be impaired by planned pressure reductions in operation and/or the replacement of ferrous mains with plastic ones. Both factors limit the amount of noise generated by leaks and subsequently reduce the acoustic logger's capacity to ‘hear’ the leaks.
Over the last decade, leakage detection has been the focus of a significant amount of research. A variety of techniques, including inverse transient analysis, Bayesian identification method, flow statistical analysis, and belief-rule-based expert system, have been applied to attempt to quantitatively identify leakage. Among the methods, some consider inverse transient modeling to be the most widespread approach. The technique is based on the deliberate generation of transient waves or impulses at one location, and the measurement of the propagated transients with highly sensitive pressure transducers at other locations in the water distribution system. The observed transient pressures are used to identify model parameters including leakage and pipe roughness.
However, the applicability of inverse transient techniques has been limited to the instantaneous small amplitude disturbances within simple reservoir-pipe-valve type configurations or reservoir-pipe-reservoir systems. To date, there are no reports of successful application of inverse transient methods to water mains distribution systems. As these networks are often highly looped and contain many valves, tanks and pumps, any induced transients will become heavily damped. Generally this prevents transient induction from being successfully used for leakage location prediction. In addition to the damping, it is also difficult to distinguish transient wave reflections caused by possible leaks from reflections caused by pipeline fittings and those arising from demand changes. There is also the risk of inducing ingress and contamination into the network from the generated transients.
Hence, there is a need for techniques for predicting likely leakage nodes locations in a hydraulic network (e.g. a water distribution system), which will enable users (e.g. engineers) to identify leaky water mains safely, quickly and cost-effectively.